هذه الوظيفة لم تعد متاحة
انتهت صلاحية هذه الوظيفة في 14/09/2026. لم تعد تقبل الطلبات.
Navigation Engineer (m/f/d)
Halian | Managed Services, Recruitment and Contract Staffing · Abou Dabi
وصف الوظيفة
About the role
We are looking for a highly motivated Navigation Engineer to develop advanced autonomous navigation capabilities for Unmanned Ground Vehicles (UGVs). You will design, implement, and optimise planning and control systems that enable reliable operation across off‑road, urban, and highway environments.
Key responsibilities
- Design, develop and optimise navigation, planning and control algorithms for high‑performance autonomous ground vehicles.
- Create accurate mathematical models of vehicle dynamics for simulation, analysis and real‑time implementation.
- Implement advanced control strategies such as adaptive, robust and predictive control.
- Research and integrate learning‑based approaches, including neural‑network system identification and reinforcement learning.
- Integrate navigation solutions with perception, localisation and vehicle software architectures.
- Conduct simulation, field testing and performance validation, analysing results to improve accuracy, robustness, safety and efficiency.
- Produce and maintain technical documentation, including system designs, algorithm descriptions, performance analyses and test reports.
Required profile
- Master's or PhD in Robotics, Control Engineering, Electrical Engineering, Computer Science, Applied Mathematics or a related field.
- Strong theoretical and practical knowledge of motion planning, vehicle control and autonomous navigation systems.
- Expertise in classical and modern control methods, system identification and optimisation.
- Hands‑on experience with ROS/ROS2 and navigation frameworks such as Nav2.
- Excellent analytical, problem‑solving and technical writing skills.
Required skills
- C++ programming
- ROS / ROS2
- Nav2 navigation framework
- Mathematical modelling and system identification
- Control theory (adaptive, robust, predictive)
- Motion planning and optimisation
- Learning‑based control (neural networks, reinforcement learning)
- Tools such as CasADi, ACADOS
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